#!/usr/bin/env python
# coding=utf-8

#Copyright 2021 Huawei Technologies Co., Ltd
#
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#
#http://www.apache.org/licenses/LICENSE-2.0
#
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License.


from StreamManagerApi import StreamManagerApi
from StreamManagerApi import MxDataInput
import os
import json
import numpy as np
import datetime
import sys


def save_infer_result(result, result_name, image_name):
    """
    save the infer result to name_1.txt
    the file content top5:
        class_id1, class_id2, class_id3, class_id4, class_id5
    """
    load_dict = json.loads(result)
    if load_dict.get('MxpiClass') is None:
        with open(result_name + "/" + image_name[:-5] + '.txt', 'w') as f_write:
            f_write.write("")
    else:
        res_vec = load_dict['MxpiClass']
        with open(result_name + "/" + image_name[:-5] + '_1.txt', 'w') as f_write:
            list1 = [str(item.get("classId")) + " " for item in res_vec]
            f_write.writelines(list1)
            f_write.write('\n')
            
def main():
    # init stream manager
    stream_manager_api = StreamManagerApi()
    ret = stream_manager_api.InitManager()
    if ret != 0:
        print("Failed to init Stream manager, ret=%s" % str(ret))
        return

    # create streams by pipeline config file
    with open("efficientnetb5.pipeline", 'rb') as f:
        pipeline_str = f.read()
    ret = stream_manager_api.CreateMultipleStreams(pipeline_str)


    if ret != 0:
        print("Failed to create Stream, ret=%s" % str(ret))
        exit()

    # Construct the input of the stream
    data_input = MxDataInput()
    
    dir_name = sys.argv[1]
    res_dir_name = sys.argv[2]
    file_list = os.listdir(dir_name)
    if not os.path.exists(res_dir_name):
        os.makedirs(res_dir_name)

    for file_name in file_list:
        file_path = os.path.join(dir_name, file_name)
        if file_name.endswith(".JPEG") or file_name.endswith(".jpeg"):
            portion = os.path.splitext(file_name)
            with open(file_path, 'rb') as f:
                data_input.data = f.read()
        else:
            continue
        
        empty_data = []

        stream_name = b'im_efficientnetb5'
        in_plugin_id = 0
        unique_id = stream_manager_api.SendDataWithUniqueId(stream_name, in_plugin_id, data_input)
        if unique_id < 0:
            print("Failed to send data to stream.")
            exit()
        # Obtain the inference result by specifying stream_name and unique_id.
        start_time = datetime.datetime.now()
        infer_result = stream_manager_api.GetResultWithUniqueId(stream_name, unique_id, 3000)
        endtime = datetime.datetime.now()
        print('sdk run time: {}'.format((endtime - start_time).microseconds))
        if infer_result.errorCode != 0:
            print("GetResultWithUniqueId error. errorCode=%d, errorMsg=%s" % (
                infer_result.errorCode, infer_result.data.decode()))
            exit()
        # print the infer result
        infer_res = infer_result.data.decode()
        print("process img: {}, infer result: {}".format(file_name, infer_res))
        
        save_infer_result(infer_result.data.decode(), res_dir_name, file_name)

    # destroy streams
    stream_manager_api.DestroyAllStreams()

if __name__ == '__main__':
    main()

